Descriptif

Convex optimization and optimal control (MAA 309) covers: basic functional analysis tools, projection on Hilbert spaces, duality; convex sets and their topological properties, convex functions, Polarity, convex duality, Hahn-Banach and min-max theorems; convexity and differentiability; convex optimization (Kuhn-Tucker), linear programming; calculus of variations, Pontryagin maximum principle, mixed inequality constraints, state constraints; dynamic programming : from discrete to continuous time, linear quadratic regulator; discrete time stochastic control, introduction to differential games.